Data Scientist Interview Questions
Practice 2,964 real Data Scientist interview questions for 2026. Data Scientist interview questions drawn from Meta, Capital One, Amazon, Google, TikTok and similar employers — real questions from actual interviews with detailed solutions — designed to accelerate your interview preparation for product analytics, ML and production data roles. This collection emphasizes the practical skills interviewers test: SQL and data manipulation, experiment design and A/B testing, statistical reasoning, Python coding for data problems, model evaluation and feature engineering, plus machine-learning system tradeoffs and metric design. What’s distinctive about modern data-science loops is the blend of product thinking and reproducible ML: expect hands-on SQL tasks and funnel analysis in screens, deeper experiment-design and causality questions in mid rounds, and coding or modeling challenges plus ML-system discussions in senior loops. Interviewers evaluate problem framing, statistical rigor, and how you communicate decisions to product partners. To prepare, prioritize daily SQL practice (CTEs, window functions), refresh hypothesis-testing and power calculations, rehearse concise metric-driven narratives, and build a few end-to-end model or experiment stories you can explain clearly under time pressure.
"I got asked a hardcore MCM DP question and I saw it on PracHub as well. Solved that question in 5 minutes. Without PracHub I doubt I could solve it in 5 hours. Though somehow didn't get hired, perhaps I guess I solved it too fast? /s"
"Believe me i'm a student here jn US. Recently interviewed for MSFT. They asked me exact question from PracHub. I saw it the night before and ignored it cause why waste time on random sites. I legit wanna go back and redo this whole thing if I had chance. Not saying will work for everyone but there is certainly some merit to that website. And i'm gonna use it in future prep from now on like lc tagged"
"10 years of experience but never worked at a top company. PracHub's senior-level questions helped me break into FAANG at 35. Age is just a number."
"I was skeptical about the 'real questions' claim, so I put it to the test. I searched for the exact question I got grilled on at my last Meta onsite... and it was right there. Word for word."
"Got a Google recruiter call on Monday, interview on Friday. Crammed PracHub for 4 days. Passed every round. This platform is a miracle worker."
"I've used LC, Glassdoor, and random Discords. Nothing comes close to the accuracy here. The questions are actually current — that's what got me. Felt like I had a cheat sheet during the interview."
"The solution quality is insane. It covers approach, edge cases, time complexity, follow-ups. Nothing else comes close."
"Legit the only resource you need. TC went from 180k -> 350k. Just memorize the top 50 for your target company and you're golden."
"PracHub Premium for one month cost me the price of two coffees a week. It landed me a $280K+ starting offer."
"Literally just signed a $600k offer. I only had 2 weeks to prep, so I focused entirely on the company-tagged lists here. If you're targeting L5+, don't overthink it."
"Coaches and bootcamp prep courses cost around $200-300 but PracHub Premium is actually less than a Netflix subscription. And it landed me a $178K offer."
"I honestly don't know how you guys gather so many real interview questions. It's almost scary. I walked into my Amazon loop and recognized 3 out of 4 problems from your database."
"Discovered PracHub 10 days before my interview. By day 5, I stopped being nervous. By interview day, I was actually excited to show what I knew."
"I recently cleared Uber interviews (strong hire in the design round) and all the questions were present in prachub."
"The search is what sold me. I typed in a really niche DP problem I got asked last year and it actually came up, full breakdown and everything. These guys are clearly updating it constantly."
Calculate Year-1 profit margin
Year-1 Profit Margin Calculation Context You are assessing Year-1 profitability for a new vegan product line. Use the assumptions below (m = million) ...
Prove SQL proficiency with concrete outcomes
SQL Proficiency Self‑Assessment and Evidence (Technical Screen) Provide a concise self‑rating and concrete, real‑world examples that demonstrate your ...
Implement robust k-means from scratch
Implement K-Means Clustering From Scratch (Production-Ready) Context You are asked to implement K-Means clustering from scratch for a machine learning...
Implement CUDA-tiled matrix multiplication and explain architecture
CUDA FP32 GEMM Design Task Implement a high-performance CUDA kernel for matrix multiplication C = A · B where: - A is m×k, B is k×n, C is m×n - Data t...
Describe career goals and what makes good teams
For a Senior Data Scientist onsite (Uber context), answer the following leadership/behavioral prompts: 1) Describe a past project where you influenced...
Investigate Falling Successful Orders
You are interviewing for a Data Scientist role at DoorDash. In the Los Angeles market, the metric successful orders per day has declined over the last...
Assess ranking change and design experiment
A multi-account product currently orders a user's accounts by most recent visit. The product team wants to change the ranking so that accounts with th...
How would you design a Shop Ads ranking algorithm?
Context An ads ranking system serves ads via an auction. You want to uprank Shop Ads relative to Website Ads to improve user conversion and help certa...
Implement bootstrap mean and variance
Given an array of N numeric values, implement a function that uses bootstrap resampling to estimate the sampling distribution of the mean. The functio...
Measure Billboard Campaign Impact: Design, Bias, Test Strategy
Measuring Billboard Impact on Brand Awareness Scenario A marketing team launched billboard ads in several cities and wants to estimate the campaign's ...
Evaluate Key Metrics for Capital One Ad Campaign
Streaming Ad Campaign Evaluation and ROI Comparison Context You are evaluating a credit-card marketing campaign on a streaming platform. The platform ...
Identify Risks and Improve Imputation Class Implementations
Scenario You are reviewing three custom Python imputation classes intended for use in a scikit-learn workflow. Each class fills missing values column-...
Fit Linear Regression: Analyze Economic Impact of Coefficients
Scenario You are given a tabular financial dataset df where the column target is the dependent variable (e.g., next-period return or excess return), a...
Explain Shell Script for Python Virtual Environment Setup
Scenario Shell script for setting up a Python virtual environment during a tech screen Question Explain what each line of the provided shell script do...
Choose Between JOIN, BLEND, and RELATIONSHIP in Tableau
Tableau Data Modeling, Filters, and Visual Design Scenario You are preparing a Tableau dashboard for marketing managers. The dashboard must support fa...
Propose Innovative Ideas and Convince Others Effectively
Behavioral Interview Prompts (Data Scientist, Phone Screen) Context You are interviewing for a Data Scientist role with a focus on product impact, col...
Identify Pirate Themes Using Similarity Score Algorithm
Scenario Engineering wants an automated way to spot custom themes that are probably just pirate themes in disguise. Question Write Python that takes t...
Define product success metrics
Define Metrics and Experiment Guardrails for a New Consumer Feature Context (Assumption to Ground the Exercise) Assume you are launching a "Price Drop...
Design a Top Dasher experiment with interference
Experimentation: Evaluate a “Top Dasher” incentive program A delivery platform wants to launch or change a Top Dasher program (e.g., priority access t...
Define engagement metrics and analyze comment distribution
You are a Data Scientist for a video platform. A PM asks you to: 1) Define metrics for “engagement” (they want a clear metric framework they can use i...